Multi-Modal Surveillance System for Actionable Event Detection
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Solution Overview
Problem
Conventional emergency assistance techniques fail to effectively detect the severity of emergency situations and provide appropriate responses due to limitations in capturing detailed information about the incident and the individuals involved, often leading to delayed or inappropriate remedial actions.
Innovation Solution
A method and system that utilize multi-modal inputs from surveillance devices and access devices to analyze incidents of interest, identify actionable events, and notify appropriate authorities, incorporating edge servers, population registers, and network operators to gather and validate information for timely and targeted responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional techniques are used for triggering and providing assistance, then the system is simple to operate, but the ability to detect severity and capture detailed information is insufficient
Solution Approach 1:
The system segments the emergency detection process into multiple stages: initial incident detection, severity assessment, detailed information collection, and response coordination. Each stage processes specific data types and involves relevant components only when needed, enabling precise detection without requiring the entire system to be always active, thus managing complexity while improving measurement precision.
Solution Approach 2:
The system transitions from traditional single-modal detection to multi-modal analysis by incorporating various data dimensions including sensor readings, video feeds, audio signals, and communication records. This dimensional expansion enables comprehensive severity assessment and detailed information capture, resolving the contradiction between detection precision and system complexity through layered information gathering.
2Reliability
If multi-modal inputs and additional information collection are implemented, then the detection accuracy and detail capture improve, but the response time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-configuring response protocols, pre-identifying relevant authorities, and pre-establishing data collection priorities based on incident types. When an emergency is detected, these pre-prepared elements are immediately activated, enabling comprehensive multi-modal analysis without delaying the initial response, thus improving detection reliability while minimizing time loss.
Solution Approach 2:
The system implements selective data gathering by skipping non-critical information collection steps when the incident severity is low or when critical information has already been obtained. For high-severity incidents, the system rushes through essential data collection phases in parallel, obtaining only the most crucial information needed for immediate response, thereby maintaining high detection reliability while reducing overall response time.
Data Source
AI summary
The disclosure relates to method and system for detecting and notifying actionable events during surveillance. The method may include receiving initial multi-modal inputs from a geo-location during surveillance, determining an incident of interest based on an analysis of the initial multi-modal inputs, and collecting additional multi-modal inputs from at least one access device corresponding to at least one person in the geo-location upon determination of the incident of interest. The method may further include determining the actionable event based on an analysis of the initial and the additional multi-modal inputs, and providing a notification of the actionable event to one or more appropriate authorities.